The max-min hill-climbing Bayesian network structure learning algorithm

We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and search-and-score techniques in a principled and effective way. It first reconstructs the skeleton of a Bayesian network and then performs a Bayesian-scoring greedy hill-climbing search to orient the edges. In our extensive empirical evaluation MMHC outperforms on average and in terms of various metrics several prototypical and state-of-the-art algorithms, namely the PC, Sparse Candidate, Three Phase Dependency Analysis, Optimal Reinsertion, Greedy Equivalence Search, and Greedy Search. These are the first empirical results simultaneously comparing most of the major Bayesian network algorithms against each other. MMHC offers certain theoretical advantages, specifically over the Sparse Candidate algorithm, corroborated by our experiments. MMHC and detailed results of our study are publicly available at http://www.dsl-lab.org/supplements/mmhc_paper/mmhc_index.html. Editor: Andrew W. Moore     

Evolution of Texture in Grain Oriented Silicon Steels

 Goss texture or (110)[100] crystallographic orientation of the grains is typical grain structure of grain oriented silicon steel used for transformer. This type of texture is one of the most important parameters determining the magnetic properties of the laminated steel plates. The formation and growth of Goss texture in three steel samples are investigated. Two of them are prepared under laboratory conditions and one under industrial conditions. The emphasis is put on the effects of hot lamination temperature and time, primary and secondary recrystallization temperatures during cold lamination on developing of the Goss texture in correlation with other texture components. Also in all steel processing stages, the influence of the chemical composition on the occurrence of Goss texture is examined.     

The role of niobium as microalloying element in electrical sheet

The processing route of grain oriented electrical sheet was simulated by laboratory trials. Besides MnS, the effect of AIN and NbC as an inhibitor phase in 3 % silicon steel was also investigated. In the hot strip material the niobium microalloyed steel showed the highest volume fraction of the {110}<001> Goss texture at 0.3 to 0.4 mm below the surface. This superiority was maintained after cold rolling and annealing after both, one step or two step cold reduction schedules. A volume fraction of the Goss texture of more than 80 % is typical for this steel concept. It can be explained by the solubility product of NbC, which guarantees grain size control during the primary recrystallisation processes and allows the Goss texture component to grow during secondary recrystallisation, which usually follows a steel decarburisation. Consistent with the highest volume fraction of Goss texture, the core losses are lowest in the sheet using NbC as an inhibitor phase.     

Operando Analysis of Reactant Conversion and Material Stability in Next‐Generation Batteries

Latest advances on operando analysis in the field of next‐generation battery research are highlighted by means of three examples: recording the pressure change and performing X‐ray diffraction analysis of metal‐oxygen batteries allows to gain detailed understanding of the main reactions and side reactions; analyzing a solid electrolyte in a hot‐press setup allows to monitor crystallization and stability during its synthesis. Since batteries are (electro)chemical reactors, the benefit of using the introduced operando techniques for classical reaction engineering is highlighted thereof.     

Numerical solution of the parabolic multicomponent convection–diffusion mass transfer equations by a splitting method

The splitting method used in a previous study for the numerical solution of mass transfer equations in ternary systems is generalized to mixtures with n-components. The diffusion coefficients are considered constant. Theoretical results about the stability of the method are presented, as well as numerical simulations for mixtures with n?=?4, 5, and 6. The numerical experiments confirmed the theoretical results and show good numerical performances. Moreover, multicomponent diffusion effects without an imposed concentration gradient are investigated for mixtures with n?=?4, 5, and 6 components.     

Ferroelectric-to-Paraelectric Phase Transition in Barium Titanate Ceramics Investigated by Pyrocharge Measurements

Temperature dependencies of the pyrocharge were recorded in view of investigating the ferroelectric-to-paraelectric phase transition in barium titanate ceramics with average grain sizes between 0.5 m and 20 m. The transition temperature decreased with decreasing the grain size. The relatively small shift of the Curie temperature detected in these pyrocharge experiments suggests that internal stresses are the main cause of the observed grain size effects.     

Identification of geometrical shapes in paintings and its application to demonstrate the foundations of geometry in 1650 B.C.

In this paper, an original general methodology is introduced to establish whether a handmade shape corresponds to a given geometrical prototype. Using this methodology, one can decide if an artist had the intention of drawing a specific mathematical prototype or not. This analysis is applied to the 1650 B.C. wall paintings from the prehistoric settlement on Thera, and inferences of great archaeological and historical importance are made. In particular, strong evidence is obtained suggesting that the spirals depicted on the wall paintings correspond to linear (Archimedes) spirals, certain shapes correspond to canonical 48-gon and 32-gon, while other shapes correspond to parts of ellipses. It seems that the presented wall paintings constitute the earliest archaeological findings on which these geometrical patterns appear with such remarkable accuracy.     

CNTs in Optoelectronic Devices: New Structural and Photophysical Insights on Porphyrin‐DWCNTs Hybrid Materials

The preparation and physical characterization of diverse porphyrin‐derived double‐walled carbon nanotubes (DWCNTs) conjugates are described. A porphyrin molecule is covalently linked and physically adsorbed to COOH‐derived DWCNTs. The photophysical properties of all porphyrin‐CNTs derivatives are studied in solution and in polymeric matrices. Definitive experimental evidence for photoinduced electron and/or energy transfer processes involving the porphyrin chromophores and the CNT wall is not obtained, but solid‐state UV‐vis absorption profiles display electronic transitions fingerprinting J‐ and H‐ type aggregates, where porphyrin molecules intermolecularly interact “head‐to‐tail” and “face‐to‐face”, respectively. In parallel, molecular modeling based on force‐field simulations is performed to understand the structure of the porphyrin‐CNTs interface and the nature of the interactions between the porphyrins and the DWCNTs. Finally, multilayered ‐ type devices are fabricated with the aim of investigating the interaction of the porphyrin‐derived DWCNTs with poly(3‐hexylthiophene)‐pyrene matrices containing small amounts of 1‐[3‐(methoxycarbonyl)propyl]‐1‐phenyl‐[6.6]C₆₁.